Orpheus 3b FT Q2 K.gguf

🚀 Orpheus-3b-FT-Q2_K

Orpheus-3b-FT-Q2_K is a quantized Text-to-Speech model, offering efficient and high - quality speech synthesis with support for multiple voices and emotional expressions.

✨ Features

• Multiple Voice Options: It provides 8 distinct voice options with different characteristics.
• Emotion Tag Support: Supports emotion tags like laughter, sighs, etc., adding expressiveness to speech.
• CUDA Acceleration: Optimized for CUDA acceleration on RTX GPUs, enabling efficient inference.
• High - Quality Audio: Produces high - quality 24kHz mono audio.
• Conversational Naturalness: Fine - tuned for conversational naturalness.

📦 Installation

This quantized model can be loaded into any of these LLM inference servers:

• GPUStack - GPU optimised LLM inference server (My pick) - supports LAN/WAN tensor split parallelisation
• LM Studio - Load the GGUF model and start the local server
• llama.cpp server - Run with the appropriate model parameters
• Any compatible OpenAI API - compatible server

💻 Usage Examples

Basic Usage

This model is designed to be used with an LLM inference server that connects to the [Orpheus - FastAPI](https://github.com/Lex - au/Orpheus - FastAPI) frontend, which provides both a web UI and OpenAI - compatible API endpoints.

Quick Start

1. Download this quantized model from [lex - au's Orpheus - FASTAPI collection](https://huggingface.co/collections/lex - au/orpheus - fastapi - 67e125ae03fc96dae0517707).
2. Load the model in your preferred inference server and start the server.
3. Clone the Orpheus - FastAPI repository:

git clone https://github.com/Lex - au/Orpheus - FastAPI.git
cd Orpheus - FastAPI

4. Configure the FastAPI server to connect to your inference server by setting the ORPHEUS_API_URL environment variable.
5. Follow the complete installation and setup instructions in the [repository README](https://github.com/Lex - au/Orpheus - FastAPI).

Audio Samples

You can listen to the model in action with different voices and emotions:

Default Voice Sample

Leah (Happy)

Tara (Sad)

Zac (Contemplative)

Available Voices

The model supports 8 different voices:

• tara: Female, conversational, clear
• leah: Female, warm, gentle
• jess: Female, energetic, youthful
• leo: Male, authoritative, deep
• dan: Male, friendly, casual
• mia: Female, professional, articulate
• zac: Male, enthusiastic, dynamic
• zoe: Female, calm, soothing

Emotion Tags

You can add expressiveness to speech by inserting tags:

• <laugh>, <chuckle>: For laughter sounds
• <sigh>: For sighing sounds
• <cough>, <sniffle>: For subtle interruptions
• <groan>, <yawn>, <gasp>: For additional emotional expression

🔧 Technical Details

📚 Documentation

Limitations

• Currently supports English text only.
• Best performance achieved on CUDA - compatible GPUs.
• Generation speed depends on GPU capability.

License

This model is available under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE - 2.0).

Citation & Attribution

The original Orpheus model was created by Canopy Labs. This repository contains a quantized version optimised for use with the Orpheus - FastAPI server.

If you use this quantized model in your research or applications, please cite:

@misc{orpheus - tts - 2025,
  author = {Canopy Labs},
  title = {Orpheus - 3b - 0.1 - ft: Text - to - Speech Model},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/canopylabs/orpheus - 3b - 0.1 - ft}}
}

@misc{orpheus - quantised - 2025,
  author = {Lex - au},
  title = {Orpheus - 3b - FT - Q2_K: Quantised TTS Model with FastAPI Server},
  note = {GGUF quantisation of canopylabs/orpheus - 3b - 0.1 - ft},
  year = {2025},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/lex - au/Orpheus - 3b - FT - Q4_K_M.gguf}}
}